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--- tags: - yolov5 - yolo - vision - object-detection - pytorch library_name: yolov5 library_version: 7.0.6 inference: false dataset: type: keremberke/license-plate-object-detection name: keremberke/license-plate-object-detection split: validation metrics: - type: precision # since mAP@0.5 is not available on hf.co/metrics value: 0.9882982754936463 # min: 0.0 - max: 1.0 name: mAP@0.5 ---

Object detection
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Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

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